Reducing Agricultural Tariffs versus Domestic Support: What’s More Important for Developing Countries?∗

Bernard Hoekman† ‡

Francis Ng† Marcelo Olarreaga † ‡

Abstract High levels of protection and domestic support for farmers in developed countries significantly affect many developing countries, both directly and through the price-depressing effect of agricultural support policies. High tariffs—in both rich and poor countries—and domestic support may also lower the world price of agricultural products, benefiting net importers. This paper assesses the impact of reducing tariffs and domestic support for a sample of 119 countries. Least developed countries (LDCs) are disproportionately affected by agricultural support policies. More than 18 percent of LDC exports are subject to domestic support in at least one WTO member, as compared to only 9 percent of their imports. For other developing countries the figures are around 4 percent for both their exports and imports. Thus, the prevailing pattern of trade suggests the world price-reducing effect of agricultural domestic support policies may induce a welfare loss in LDCs. We develop a simple partial equilibrium model of global trade in commodities that benefit from domestic support in at least one WTO member. Our simulation results suggest there will be large differences between LDCs and other developing economies in terms of the impact of a 50 percent cut in tariffs as compared to a 50 percent cut in domestic support. Developing countries as a group would suffer a welfare loss from a cut in support, while LDCs would experience a small gain. For both groups of countries, tariff reductions by WTO members—including own liberalization—will have a positive effect on welfare. The results illustrate both the importance of focusing on tariffs as well as subsidies, and the need for complementary actions to allow a domestic supply response to occur in developing countries if world prices rise. JEL classification: D58, F13, F14, Keywords : Agriculture, WTO, trade negotiations, tariffs, subsidies, developing countries World Bank Policy Research Working Paper 2918, October 2002 The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org.

∗ We are grateful to Ataman Aksoy, Gopi Gopinath, Harry de Gorter, Ashok Gulati, Tim Josling, Will Martin and participants at the conference “The Developing Countries, Agricultural Trade and the WTO,” Whistler June 16-17, 2002 for helpful comments and suggestions. Thanks also to Lili Tabada for assistance in constructing the database; to Morvarid Bagherzadeh, Bijit Bora and Wojciech Stawowy for estimates of ad-valorem equivalents of specific tariffs. † Development Research Group, World Bank, 1818 H Street, NW, Washington, DC, USA. ‡ Centre for Economic Policy Research, London, UK.

1

1 Introduction

Developing country agricultural exports are limited by high tariffs in many countries. Domestic

support for farmers in high- income economies also hurts developing country exporters to the

extent that it boosts domestic production, depresses world prices, exacerbates the volatility of

world prices and reduces the scope for import competition. High tariffs and domestic support

policies may, however, benefit net importers of agriculture products in developing countries by

providing access to the subsidized commodities at lower prices.1 Thus, as is well known, national

interests regarding reform of OECD agricultural trade and support policies will differ. However,

most analyses conclude that the overall gain to developing countries from reforming agricultural

policies greatly outweighs the potential costs to countries that are significant net importers of

subsidized agricultural products.

Starting in 2000, negotiations were launched in the WTO to further reduce intervention in

agricultural markets. These negotiations focus on both subsidy policies and border protection

(tariffs and tariff rate quotas). An important policy question confronting developing countries is

to determine which instruments of agricultural protection are most detrimental to their interests.

In this paper we attempt to shed some light on this issue by assessing the relative impact of

tariffs and domestic support policies on exports and welfare of developing countries.

Specifically, we analyze the impact of a 50 percent global reduction in agricultural tariffs and

compare this to a 50 percent cut in domestic support.2 Our objective is to assess where

negotiating efforts in the context of the current WTO negotiations on agriculture might be best

directed.

We find that in welfare terms, tariffs matter significantly more than subsidy policies—

tariff reductions generate welfare gains that are substantially greater than reductions in support

policies.3 In large part this is because of high tariff peaks in OECD countries and because

developing countries also use tariffs to protect domestic production. As is almost always the

case, when it comes to trade policy reform, the principle ‘what you do determines what you get’

applies. This does not imply that negotiations should therefore emphasize tariffs over domestic

1 This potential national welfare benefit is offset by the higher price volatility created by support policies as country specific shocks may be transferred to world markets. In this paper we ignore the extent to which price volatility is transmitted to world markets. 2 The policy simulation can be motivated by a conservative interpretation of the Doha declaration: “….we commit ourselves to comprehensive negotiations aimed at: substantial improvements in market access, reduction of, with a view to phasing out, all forms of export subsidies; and substantial reductions in trade-distorting domestic support” (WTO Doha Ministerial Declaration, para 13, November 2001).

2

support policies. A major political economy problem confronting WTO negotiators is to create

incentives for countries to liberalize agricultural trade. Opposition to further agricultural trade

liberalization in many developing countries is bolstered by the continued large-scale support for

OECD farmers. Past experience has demonstrated that the gains from own liberalization may be

attenuated because of the market segmenting effect of OECD subsidy policies, and in some

instances—e.g., India—liberalization proved to be politically unsustainable because of large

world price swings and import surges of subsidized commodities (Gulati and Narayanan, 2002).

Substantial reduction in OECD agricultural support policies is therefore not just important for

developing countries in its own right—in that it generates direct benefits for the many economies

that are (potential) net exporters—but is critical to support efforts by developing country

governments to pursue domestic reforms. That is, subsidy reforms in OECD countries are

necessary, but not sufficient, for developing countries to reap significant gains from the current

WTO negotiations on agriculture.

In contrast to many quantitative analyses of the effects of agricultural trade policies, we

use a partial equilibrium framework to estimate the impact of policy changes for a sample of 119

countries on world prices of agricultural commodities that benefit from domestic support in at

least one WTO member. We limit the analysis to products that benefit from domestic support in

order not to bias our findings. Because most countries apply tariffs to all agricultural products,

not just those that are subsidized, any comparison of the effect of reducing tariffs on all

agricultural goods with a reduction in support policies would conclude that tariffs are more

important for developing countries. The partial equilibrium approach allows us to assess the

effects of policy changes on individual countries, including low income and least developed

economies that are of particular concern to the development community. The majority of these

countries are generally subsumed in regional aggregates in applied general equilibrium models.

The partial equilibrium approach also allows us to use disaggregated trade and protection data—

we work at the 6-digit level of the Harmonized System.4

3 Note that export subsidies are left outside the analysis but these are relatively small as they represent only 8-10 percent of total domestic support. 4 For recent CGE studies focusing on the same question see Beghin, Roland-Holst and van der Mensbrugghe (2002), Dimaranan, Hertel and Keeney (2002) and Rae and Strutt (2002). These studies obtain qualitatively similar results (i.e., border barriers matter more than domestic support).

3

2 Tariffs and domestic support in agriculture

Agricultural products are often subject to tariff peaks that are 100 percent or higher (Hoekman,

Ng and Olarreaga, 2002). The average MFN tariff that is applied to agricultural products varies

substantially across countries, but in the majority of OECD countries is more than double the

average that applies for manufactures. In addition to tariffs, many high- income countries

subsidize domestic agriculture. WTO data indicate that there are 158 commodities at the 6-digit

level of the Harmonized System (HS) that benefit from domestic support in at least one WTO

member. Large-scale use of domestic support is primarily found in OECD countries, especially

the EU, Japan and the United States. Industrialized countries account for 88 percent of total

domestic support payments; if South Korea and transition economies such as Poland are

excluded, developing countries account for only 10 percent of total support reported to the WTO

during 1995-6 (Table 1). Major subsidizers among developing countries include Brazil, Thailand

and Venezuela. Not surprisingly, least developed countries (LDCs) report virtually no domestic

support. Meat, dairy, cereals and sugar account for the lion’s share of domestic support,

representing almost 75 percent of all reported non-exempt domestic support (WTO categories

DS4-9) (Table 2).

The average tariff on these subsidized products is around 18 percent, with peaks in the

100-200 percent range for many countries (Table 3). Average tariffs are relatively uniformly

distributed across major product categories, with the highest applying in dairy and sugar (and

alcoholic beverages—a special case given use of tariffs for revenue and cultural purposes) (Table

4). These are also the sectors that have the highest levels of domestic support. A number of

countries make intensive use of specific tariffs for agricultural imports. One consequence of this

is that statutory average ad valorem MFN tariffs understate the level of tariff protection,

especially for the EU and Japan. 5 In this paper we use estimates of ad valorem equivalents of

specific tariffs for the 158 tariff lines on which the analysis focuses, drawing on data reported in

Stawowy (2001) and OECD (2000) at the tariff line level. Given that estimates of ad valorem

equivalents for Switzerland are incomplete and unreliable, we have excluded this country from

the analysis (Switzerland relies almost completely on specific tariffs).

The global pattern of protection and support to agriculture will have differential impacts

on countries depending on whether they are net producers or consumers of the commodities

5 Fontagné et al. (2002) report that the EU, Japan and the US have 1,059, 418 and 1,148 six-digit tariff lines that are subject to specific tariffs.

4

affected. A first cut at identifying the likely implications of protectionist policies for individual

countries is to calculate the relative importance of exports and imports of the products that are

subsidized by at least one WTO member. Such data reveal that LDCs are potentially much more

affected than other countries: 18 percent of their exports on average comprise goods that are

subsidized in at least one WTO member, compared to 3-4 percent for other countries (Table 5).

A similar observation holds for imports—nine percent of LDC imports involve products that are

subsidized, compared to 3-4 percent for other countries. For many LDCs the potential incidence

of subsidies is therefore very high. Indeed, for countries such as Benin, Burkina Faso, Burundi,

Chad, Malawi, Mali, Rwanda, Sudan, Tanzania, Uganda and Zimbabwe, 60 to 80 percent of total

exports comprise goods that are subsidized by one or more WTO members. Given that these are

also countries that tend to have preferential—mostly duty-free—access to the European market

(through the GSP and Everything But Arms initiative), this suggests subsidies are an important

issue for WTO negotiations (as subsidies are not covered by preferential access agreements).6

However, this ignores the depressing effects of tariffs by major WTO members on world prices,

as well as the impact of own tariffs—issues that are explored empirically below.

Table 5 also identifies countries where the ratio of imports of subsidized goods to total

imports is higher than the ratio of “affected” exports to total exports. In such cases it is possible

that global liberalization may have short run negative effects on the terms of trade and/or welfare

insofar as the prices of imports are lowered because of subsidies. Countries where the balance is

tilted towards imports of subsidized commodities comprise countries at very different levels of

per capita incomes. They include Bangladesh, Comoros, Egypt, Gambia, Guinea, Jordan, Korea,

Maldives, Mauritania, Morocco, Nigeria, Oman, Saudi Arabia, Senegal, Taiwan, Tunisia and

Venezuela.

The agricultural domestic support numbers reported to the WTO comprise a mix of

instruments and measures. The major distinction that is made is between measures that are

exempted from WTO reduction commitments under the Uruguay Round Agreement on

Agriculture and those that are not. The former include so-called green box support, measures

whose use is permitted for developing countries and payments under production limiting

6 It is difficult to assess to which extent EBA offers actual preferential access to LDCs as rules of origin and other non-tariff barriers may actually erode the preferential access granted on paper. In the case of the US initiative for Sub-Saharan Africa (AGOA), there is data made publicly available on the actual gains for African countries and these tend to be small (Mattoo, Roy and Subramanian, 2002). In the case of Europe, Brenton and Manchin (2002) show evidence that EU preferential access schemes have offered limited benefits due to restrictive rules of origin.

5

programs (including the blue box).7 The latter include measures that are deemed to directly

support production. As our interest in this paper is to compare the effect of border protection

(tariffs) with domestic subsidy-type support on a product-by-product basis, we use the WTO

Aggregate Measure of Support (AMS) data, as this does not include the effect of border barriers.

We recognize that there are a number of limitations associated with the AMS data.8 One problem

is that the time period for which data are available is short and reporting is incomplete, especially

for more recent years. This is discussed further in the data annex. Another problem is that the

economic relevance of the AMS time series is limited given the use of the fixed 1986-88

benchmark for purposes of calculating price support. However, given that the econometric and

simulation work is done for one point in time (the average for 1995-1998), this should be less of

a problem in this paper.

3 Analytical framework

To estimate the impact that a reduction in tariffs and/or domestic support may have on exports

and welfare we use a simple partial equilibrium model. World markets are assumed to be

perfectly competitive and integrated, in the sense that there is no further scope for arbitrage

across countries. Products traded in world markets under the same 6-digit HS classification are

considered to be perfectly homogenous.9 Each 6-digit HS product category represents only a

small share of the economy, so that the effect on other product markets of changes in a particular

category is negligible.10

Import demand for each HS-6-digit product of country c is given by:

( )( )[ ]

11dd

cccw

cc

stp

am

λετ++= (1)

7 See Hoekman and Kostecki (2001) for a review of the WTO Agreement on Agriculture. 8 See de Gorter (2002) for a careful discussion of problems associated with measurement of the AMS. 9 In practice there may be heterogeneity even at the 6-digit level in that imports (or exports) may be of a higher quality than exports (imports). In some developing countries high quality imports may have only a limited degree of competition with low quality domestic production. If so, this will imply that traditional measures of protection such as the ratio of import to domestic price for the product will overstate the magnitude of protection. In this paper we use only tariffs, not the nominal rate of protection. 10 The setup is very similar to the one in Zietz and Valdés (1986) and Hoekman, Ng and Olarreaga (2002). The latter discuss some of the caveats associated with the use of this type of model. Note that no account is taken of issues such as the potential impact of exchange rate overvaluation, indirect taxes and other factors that may result in an overall anti-agriculture bias and thus offset the effect of tariff protection and/or subsidy policies. Schiff and Valdes (1998) suggest that in many developing countries anti-agriculture bias due to such policies has declined, implying that direct instruments such as tariffs and subsidies are the major determinants of the magnitude of protection.

6

where dε is the import demand elasticity, wp is the price in the “world” market; ct is the tariff

in country c; cτ is the average transport cost from country c to the “world” market;11 cs is the

producer support in country c;12 dλ is the elasticity of import demand to the producer support;

and ca is a demand parameter in country c that captures size and all other factors influencing

import demand.

Export supply for each HS-6-digit product of country c is given by:

( )s

s

cc

wcc s

pbx λ

ε

τ

+

=1

(2)

where sε is the export supply elasticity, sλ is the elasticity of export supply with respect to

domestic support;13 and cb is a supply parameter that captures size and other determinants of

export supply. The transport cost to world markets is also common among exporters and

importers of the same product. The presence of tariffs and domestic support measures may lead

to both imports and exports of a homogenous product for a given country.

We are forced by data constraints to assume that the import demand and export supply

elasticities for products, as well as the import and export elasticities with respect to domestic

support, are identical for all countries in the sample. This has implications for the implied

domestic supply and demand elasticities of domestic support across the countries in our dataset.

For example, if these were relatively similar across countries, and consumption were to be only

marginally affected by changes in domestic support, then import demand elasticities should vary

across countries depending on the ratio of domestic production to exports. Given that production

and consumption data are not available at the six-digit level of the Harmonized System, we

cannot estimate underlying domestic demand and supply elasticities. In the empirical analysis

below we test to what extent the assumption of identical elasticities across countries has

implications for our results.

11 This explains differences in import prices across different countries as observed in the data. 12 We attribute to countries with no domestic support a $1 value for the import demand function not to be undetermined. 13 Again, we attribute to countries with no domestic support a $1 dollar value for the export supply function not to be undetermined. The same caveat as in the previous footnote applies.

7

The equilibrium world price is obtained by solving for the world price in the world

market clearing condition, i.e.,

( )( )[ ]

( )

)(1

1

110argsol

ds

s

s

dd

w

c c

cc

c ccc

c

cc

cc

p

ew

sb

st

a

xmp

εε

ε

λ

λε

τ

τ

+

+

++=

=−=

∑

∑∑∑ (3)

The change in the world equilibrium price following a reduction in tariffs is obtained by taking

the total differential of (3) with respect to cτ . The percentage change in the world price with

respect to a common percentage change in tariffs in all countries is then:

( ) ( )( )[ ]

( )( )[ ]

++

+++

+−=

∑

∑

c ccc

c

c ccc

c

c

c

sd

dew

dd

dd

st

ast

at

t

tp

λε

λε

τ

τ

εε

ε

11

111ˆˆ (4)

where a “hat” (^) denotes the percentage change in the variable.

Similarly, the percentage change in world prices following a common percentage change

in subsidies, s , is given by:14

( )( )[ ]

( )( )[ ]

( )

( )

+

+

−

+

++

++

−

+−=

∑

∑

∑

∑

c c

cc

c c

cc

c

c

s

c ccc

c

c ccc

c

c

c

dsd

ew

s

s

s

s

dd

dd

sb

sbs

s

st

ast

as

s

sp

ε

λ

ε

λ

λε

λε

τ

τλ

τ

τλ

εε

1

1

1

11

11

1

ˆˆ (5)

The change in export revenue and import revenue associated with a change in tariffs or domestic

support is given by:

14 Here we do not change the $1 domestic support subsidy attributed to countries with no domestic support.

8

( )

( )c

cc

d

c

cdw

drc

c

cc

sw

src

ss

st

ttpm

ss

spx

1ˆ

1ˆˆ1ˆ

1ˆˆ1ˆ

−−

+−−−=

−++=

λεε

λε (6)

where rcx is the percentage change in export revenue in country c, and r

cm is the percentage

change in import revenue in country c. Note that if there is no producer support or tariffs in

country c, then there will be no changes in export revenue or import revenue in this country, a

part from those induced by the change in world price after other countries have reduced their

tariffs or producer support.

Finally, one can measure the change in welfare in an importing and exporting country by

taking the integral of the import demand and export supply functions with respect to world prices

and tariffs (it is assumed that domestic support is just a transfer from government revenue to

producers). The change in exporters and importers welfare relative to their initial export and

import revenue is then given by:

( )( )

( )( )

c

crcc

c

cc

c

cw

dmc

c

cws

xc

tt

tmt

ss

stt

ttp

w

ss

spw

d

d

d

s

s

++

+

−++

−

+

++−

=

−+−+

+=

−

+

1ˆˆ

1ˆ11

11

1ˆˆ1

11

1ˆ

1ˆ11ˆ1

11

ˆ

1

1

λε

ε

λε

ε

ε

(7)

where xcw is the change in welfare in an exporting country relative to the initial export revenue;15

mcw is the change in welfare in an importing country relative to the initial import revenue. The

first term on the right-hand-side of mcw is the change in import consumer surplus and the second

term is the change in tariff revenue. Note that changes in welfare in (7) take into account shifts of

domestic import demand and export supply functions following changes in domestic tariffs and

domestic support (when relevant). The overall change in welfare can be obtained by adding up

15 Note that is exactly equal to the percentage change in world prices if the elasticity of export supply is nil.

9

the two expressions in (7) after normalizing the two terms to the same base (either exports,

imports, total trade, or in $ per capita terms).

4 Empirical methodology

The empirical methodology consists of three steps. First we estimate import demand and export

supply elasticities with respect to prices and subsidies (i.e., sdsd λλεε and ,, ). We then

calibrate the demand and supply parameters (i.e., cc ba and ) for each country and product (at the

HS six-digit level). Finally, we use the elasticities and calibrated parameters to measure the

changes in world prices, export revenue, import revenue and welfare following a 50 percent

reduction in agriculture tariffs and domestic support in all countries.

To estimate the different elasticities, we could simply estimate the import demand and

export supply functions (1) and (2). However, these are simultaneously determined in any

country c. Moreover, we do not observe “world” prices, but only export and import unit values in

each country, which include transport costs. If traded quantities are measured with error (which

is likely as customs generally are more concerned with value), unit values will also be measured

with error, which may bias our results.16 To avoid these problems we first choose units so that

the average world price of each product for the period 1995-1998 is equal to 1. We then estimate,

across countries and products, the net import demand function as the log difference of import

demand and export supply for each country (measured in value terms due to the choice of units)

in each country. Note that the world prices will then drop from this specification as

0)1log()log( ==wp .

Using the import demand and export supply functions in equations (1) and (2), we obtain

the following estimating equation:

( ) ( ) ( ) ( ) ( )( ) ( ) ( ) ( )c

sdc

sd

cd

ccrr

s

tbaxm

log1log

1logloglogloglog

λλτεε

ε

+−+−

−+−−=− (8)

16 Note that it is not clear what can be use as an instrument for unit values at the six digit level of the harmonized system.

10

As controls for cc ba and we use GDP and population in each country. Product dummies at the

HS six-digit level are also included.17

In the second step, using the elasticities estimated using a stochastic version of (8), we

calibrate cc ba and using (1) and (2). The estimation of changes in world prices, import revenue,

export revenue and welfare is done using equations (4) to (7).

Data on import and export revenue as well as tariffs are available from the World Bank

WITS database at the six digit of the harmonized system. The measure of domestic support that

is used is the WTO Aggregate Measure of Support (AMS), obtained from the WTO, based on

member notifications (WTO document G/AG/NG/S/1, April 13, 2000). The AMS data are based

on an arbitrary product classification and were concorded to the HS classification (see the Data

Annex).

Only 30 WTO members have made domestic support reduction commitments under the

Agreement on Agriculture (AoA), but all members are required to notify domestic support.

Compliance is weak—in 1995 only 75 percent of all WTO members that were required to notify,

did so. In 1996 and 1997 the coverage drops to around 50 percent; for 1998 only 28 percent of

WTO members had notified by March 2000. However, most countries that did not notify in

1997-8 had very little or no support in 1995-6, so the coverage of the data spans the major users.

To address the incomplete reporting problem, we use the average AMS reported for whatever

years are available. The empirical analysis therefore involves an unbalanced panel.

Domestic support notified to the WTO includes exempt and non-exempt measures. There

are nine categories of support, designated DS1 through DS9. DS1 covers measures that WTO

members have placed in the “green box”, and are therefore exempt from reductions (the green

box categories are defined in Annex 2 of the AoA). DS2 comprises measures that, for developing

countries, are exempt from reduction commitments under Article 6.2 of the AoA relating to

development programs. DS3 is used to signify direct payments under production- limiting

programs under Article 6.5 of the AoA. Categories DS4 to DS9 comprise measures that are not

necessarily exempt from reduction commitments. DS4 refers to non-exempt support that is

below the de minimis level (as set out in Article 6.4 of the AoA). The remaining categories

included in the total AMS of WTO members include market price support (DS5), non-exempt

17 A justification for the introduction of GDP and population as control variables could be associated with the idea that import demand for agriculture products is a function of the level of development in each country. Alternatively, the constrained version of (8) using GDP per capita could be interpreted as capturing the capital labor ratio of each country. The constrained specification yields results within one standard deviation of those reported later in Table 6.

11

direct payments (DS6), other product-specific support (DS7), and any support measured via the

Equivalent Measurement of Support methodology (DS8). Finally, where relevant, a total figure

for non-product-specific support is also given (DS9).18

Two problems with the estimation of equation (8) are (i) that transport costs are not

directly observable and (ii) that we cannot retrieve the elasticity of import demand and export

supply with respect to domestic support, but only its sum. Assuming that transport costs to the

world market are equal for exporters and importers, these costs can be proxied by the ratio of

export and import unit values. As long as the measurement error in unit prices is identical for

exports and imports the problems described above are addressed. As regards the second issue, we

assume that elasticitie s of import demand and export supply with respect to domestic support are

equal.19

5 Results

We first focus on the estimation of the price and domestic support elasticity of export supply and

import demand and then turn into the results of the simulation exercise.

Estimating elasticities

Table 6 reports the results of the estimation of equation (8) using different measures of domestic

support. In column 1 results are reported using notifications by WTO members of non-exempt

support (this corresponds to categories DS4 to DS9 according to WTO notification procedures).

These are (generally) product specific and include market price support (calculated according to

the methodology in Annex 3 of the Uruguay Round Agreement on Agriculture) and non-exempt

direct payments (denoted 94−DScs ). Column 2 reports results using notifications on exempt

domestic support (this corresponds to categories DS1 to DS3 according to WTO notification

procedures). These are non-product specific and include measures which WTO members have

placed in the “green box”, measures that are exempt in developing countries and direct payments

18 CGE analyses are usually based on the PSE data compiled by the OECD, which not only includes price support measures, but, more importantly, does not correspond to the typology of measures that are the focus of WTO negotiations (e.g., production vs. other (decoupled) support. See Dimaranan (2002) for a noteworthy attempt to map PSE support data into types of policy measures as a function of the factor of production that is supported. 19 Note that if the ratio of production to exports and imports is different, then one should expect different elasticities of import demand and export supply for a given elasticity of domestic supply to domestic support. One way to (partially) reconcile this with our results is to recognize that the change in domestic support will also affect domestic demand through changes in domestic and world prices. In the estimations, we test the robustness of our results by varying the elasticities with respect to domestic support on the demand and supply side.

12

under production- limiting programs (the ‘blue box’). Such non-product specific support is

allocated for purposes of estimation across products using the distribution of domestic support

commitments by product (the idea being that exempt support is likely to be higher in sectors

where non-exempt support is larger following a political-economy logic). This type of domestic

support is denoted as 31−DScs . Column 3 reports results of the estimation of (8) with the two types

of domestic support entering separately. Finally, Column 4 reports results using the sum of both

types of support.

Given the unbalanced nature of the data set, we work with a between estimator, using as

observations the average across the four year period for which support data are available, rather

than the annual data (i.e., the sample is a cross-section of countries and products).20 The

elasticities are then identified using the cross-country variation for each product.21 Results across

the four specifications generally yield an elasticity of import demand around 1.36-1.45 and an

elasticity of export supply around 0.19-0.28. The (sum) of the elasticities of domestic support

varies from almost 0 (in the case of DS1-3 in column 3) to 0.10 in column 1 (for DS4-9). The

fact that DS1-3 is insignificant in column 3 may be due to collinearity problems given the

methodology used to construct this variable (i.e., general domestic support is distributed across

products using product specific support commitments). When both types of domestic support are

added up in column 4, the (sum) of the elasticity of domestic support is statistically significant.

To determine whether we should work with the sum of the two types of domestic support,

we run a non- linear specification of equation (8) to test whether the two types of domestic

support can simply be added up. Results are reported below, with standard errors in

parenthesis:22

( ) ( ) ( ) ( ) ( )

( )

+−+−

−+−−+=−

−− 31

)00.0(

94

*)02.0(**)08.0(

**)05.0(**)04.0(**)04.0()42.0(

00.0log04.01log17.1

1log34.0log45.0log34.029.0loglog

DSc

DScc

cccrr

ss

tpopgdpxm

τ (9)

20 This is also due to the fact that ad-valorem equivalents of specific tariffs have only been estimated for 1999 in OECD (2000) and Stawowy (2001). 21 Thus, the variation in import and export prices across countries, which is explained by transport cost to the “world” market, allows us to identify the different elasticities. 22 A “*” indicates statistical significance at the 5 percent level; “**” indicates significance at the 1 percent level.

13

Equation (9) suggests that we should drop the general domestic support DS1-3 from the

estimation, as the coefficient on 31−DScs is not significantly different from zero. In the specification

we employ in the simulations below we therefore only include non-exempt domestic support 94−DS

cs , i.e., we use the results reported in column 1 of Table 6. Thus, the 50 percent reduction in

domestic support used in the simulations pertains only to non-exempt domestic support (as

exempt domestic support does not seem to affect trade flows and therefore should have no—or

little—impact on world prices).23

The estimation in column 1 is done across the 158 HS 6 digit commodities. We assume

these elasticities to be common across these different products. This is not necessarily the case of

course, as there may be heterogeneity across products. Table 7 reports results of the estimation in

column 1 of Table 6 letting the elasticity vary across different groups of products (a seemingly

unrelated regression technique was used to provide standard error estimates to control for a

common explanatory variable that is omitted from the regression). The first five columns in

Table 7 report the results for animal products (HS 01 to 04), vegetables, fruits and nuts (HS 6 to

9), cereals and grains (HS 10 to HS 14), processed food products (HS 15 to HS 24), and cotton

and other textile fibers (HS 50 to 53). While the variations in import demand and export supply

elasticities are quite large, the elasticity with respect to domestic support is similar across sectors

(it varies between -0.07 and -0.16). The product group-specific elasticities are used below as the

base estimates for the simulation exercises. The overall estimates in column 1 of Table 6 are

used to test for the robustness of the results.24

As mentioned, because we use the information on cross-country variation to estimate the

different elasticities, it is assumed that these elasticities do not vary across countries. If we were

to relax this constraint, the solution to the model in Section 3 would be non- linear. To determine

the restrictiveness of this assumption we estimated the equation in column 1 of Table 6 for the

developing countries only. All elasticities are within one standard deviation of the elasticities for

the whole sample (except for the import demand elasticity which is within two standard

deviations). We then estimated it for the three major users of domestic support separately: the

23 Note that exempt domestic support is generally de-linked from production and is more likely to affect the production decision rather than the level of production as measured when working with trade flows. 24 Note that for Animal products, Cereals and other grains, and Silk, Cotton & other fibers, the coefficient capturing the import demand elasticity is insignificant whereas the difference between the import demand and export supply price elasticities is significant. In these three cases, we cannot reject the assumption that the export supply elasticity is zero. We therefore set the export supply elasticities to zero in the simulations for these products and calibrate the import demand elasticities accordingly.

14

EU, Japan and the United States. The results suggest heterogeneity in the price elasticities across

countries, but the imprecision in the parameter estimates did not allow the hypothesis to be

rejected that they are equal across countries. Estimates of elasticities with respect to domestic

support were relatively homogenous (-0.08 for the EU, -0.12 for Japan and –0.10 for the United

States). Thus, the elasticity of net import demand with respect to domestic support seems to be

relatively small (around 0.1) suggesting a reduction in domestic support across WTO members is

likely to have a small impact on world prices.25

Simulation results

In our baseline simulations we use the estimated coefficients in Table 7 to calibrate import

demand and export supply in each country. Then changes in export revenue, import revenue, and

welfare following a 50 percent cut in tariffs and domestic support to farmers across all WTO

members are calculated for each country using (6) and (7). We also calculate the change in terms

of trade by weighting the changes in prices by export and import shares in each country. Recall

that the simulations are done for the 158 tariff lines at the HS 6-digit level for which at least one

country provides domestic support to its farmers. (The overall agricultural universe includes

more than 900 tariff lines at the HS 6-digit level).

Table 8 reports results on the change in export revenue, the import bill, the terms-of-trade

and welfare for the three broad country groups of a 50 percent tariff reduction or a 50 percent

domestic support reduction. Aggregate product specific and individual country results are

reported in Appendix Tables 1 and 2. The increase in trade across all country groups is much

larger for the 50 percent tariff cut than for the reduction in domestic support. Exports of

developing countries (excluding LDCs) increase by $4.2 billion, or 6.7 percent of the initial

export revenue for the 158 product categories (Table 8). LDC exports increase by $116 million

(or 3.7 percent), while industrialized country exports increase by $3.3 billion dollars (4.7

percent). There is also an increase in the import bill following the 50 percent tariff reduction. In

industrial countries the increase in imports is double the increase in exports (due both to an

25 Note that the implicit assumption here is that domestic support only affects the variable cost of farmers receiving the subsidy, as we move along the export supply and imp ort demand functions. If domestic support affects fixed costs (or the production decision), as is probably the case with subsidies that are decoupled from production, we would need to work along the domestic supply function. Data on production is not available for such a large number of countries at the disaggregated level required. This also suggests that we should be working only with non-exempt subsidies (which are generally not decoupled from production).

15

expansion in demand and higher world prices). The increase in imports in developing and least

developed countries is roughly equal to the increase in exports.26

In relative terms many developing countries see a significant expansion in exports

following a 50 percent cut in tariffs. Figure 1 plots the impact on exports of a 50 percent cut in

tariffs (in the vertical axis) and domestic support (in the horizontal axis) trade for the 121

developing and least developed countries in the sample. The vertical and horizontal lines indicate

a “zero” change in exports due to a cut in tariffs or domestic support, respectively. The highest

percentage increases in exports are found in the Caribbean and Central American region

reflecting the specialization of these countries in commodities such as edible fruits and

vegetables, processed foods and sugar—the categories that see the largest expansion in demand

in percentage terms (Appendix Table 1).27 Mauritius, Philippines and Thailand—all developing

countries that are producers of such commodities—also see increases in exports of over 10

percent. With a few exceptions such as Congo and Malawi, African countries tend to register

only limited increases in exports.

The increase in exports following a 50 percent cut in domestic support is a tenth of what

is generated by cutting tariffs (Table 8). Developing country exports increase by $0.5 billion, or

0.8 percent of the 1995-1998 average level of exports. LDC exports rise by $64 million (2

percent), while industrial countries expand exports by $314 million (0.5 percent). More striking

is the fact that the import bill decreases in developing and least developed countries after a 50

percent cut in domestic support (Figure 2). The reason for this is that world prices increase after

the cut—import demand functions being relatively elastic, the import bill necessarily decreases.

Welfare increases in all groups of countries after multilateral tariff reforms (Table 8). The

increase in welfare for developing countries generated by the 50 percent tariff cut is due not only

to increased exports, but to the liberalization that occurs in these countries (and the absence of

domestic support). In contrast, developing countries as a group would see a small reduction in

welfare following a cut in domestic support. The rela tively high tariffs that prevail in many of

these countries explain why the impact in welfare terms is so different. The potential negative

implication of a cut in domestic support illustrates the importance of also cutting tariffs.

26 Note that the increase in exports is not necessarily equal to the increase in imports at the aggregate level for two reasons. First, increases in export and import revenue are measured at customs and therefore include transport cost. Second, we did not have data for all countries, so it is assumed that the rest-of-the world also adjusts to changes in world prices.

16

In the case of LDCs the ratio of gains is quite different. Instead of a ten to one ratio of

export gains due to tariff vs. domestic support cuts, it is only two to one. Moreover, the

simulations suggest that LDCs will obtain welfare gains from both types of reform. These

differences between the two country groups reflects both the LDCs greater ‘sensitivity’ in

relative terms to OECD support policies and the pattern of production and trade in the various

products.

There is substantial heterogeneity across countries, reflecting differences in export and

import bundles. Variations in the levels of tariffs and domestic support across different products

in large trading partners also partly explain this heterogeneity. A cut of 50 percent in tariffs

generates a relatively large increase in developing country exports of edible vegetables, fruits

and nuts (HS07-08), sugar (HS17) preparations of vegetables and fruits (HS 20-21) and tobacco

(HS24). In the case of LDCs, the largest increases occur in meat (HS02), sugar and

miscellaneous edib le preparations (HS21) (Appendix Table 1).28

A large number of countries in the sample see their terms-of-trade deteriorate after a 50

percent tariff cut (Appendix Table 2). This is also the case following a 50 percent cut in domestic

support. Figure 3 plo ts the change in terms of trade following changes in tariffs and domestic

support. As before, the vertical and horizontal lines indicate a “zero” change in the terms of

trade. Changes in terms of trade seem to be positively correlated across the two types of cuts, i.e.,

countries that see their terms of trade increase after a tariff cut will also see their terms of trade

improve after a domestic support cut.

The fact that the terms-of-trade deteriorates does not necessarily imply a reduction in

welfare, given that countries own reforms will tend to increase welfare. Nonetheless in a number

of instances welfare does decline. This is the case in particular for oil producers and large net

importers such as Algeria, Bahrain, Brunei, Egypt, Gabon, Oman, Russia, Saudi Arabia, and

Venezuela. Any welfare losses are generally much smaller if the experiment is a 50 percent cut

in domestic support. Figure 4 plots the change in welfare per capita under the tariff cut against

the change in welfare per capita under the domestic support cut for the countries in the sample,

with the horizontal and vertical lines again indicating a “zero” change in welfare. Thus, countries

in the North East quadrant of Figure 2 see their welfare increase under both types of reforms.

27 To the extent that these countries enjoy tariff preferences in some products for these products, results may overstate their gains. But again, preferential access on paper does not necessarily mean actual preferences granted. Second, these are very small countries that only marginal affect the overall picture for developing countries. 28 Note that here we abstract from sanitary or phyto-sanitary barriers, as well as other non-tariff barriers that may also be hindering trade.

17

This includes Mauritius, Fiji, Belize, Guyana, Costa Rica, Uruguay, etc. There are no countries

in the South East quadrant, suggesting that there is no case where a country increases its welfare

following a cut in domestic support but sees its welfare reduced under the tariff cut. Losers under

both types of reforms include the large net importers mentioned previously.

Sensitivity analysis

Given the various assumptions made with respect to elasticities, a number of sensitivity analyses

were performed. We first re-estimated the figures in Table 8 using the elasticity estimates

provided for the whole sample in the first column of Table 6 (instead of the elasticity estimates

by product reported in Table 7). We also re-estimated the numbers of Table 8 using extreme

values (i.e., instead of half the estimated coefficient in Table 8, we use either zero or the total

value of the estimated coefficient) for the elasticities of domestic support on the import and

export side. Finally, we compared results with the case where only OECD members reduce their

tariffs and domestic support.

Using the elasticities estimated for the whole sample, the increase in exports after a 50

percent tariff cut is 25 percent lower for developing countries and 15 percent lower for LDCs.

On the other hand, the increase in exports after a 50 percent cut in domestic support is 25 percent

higher for developing countries, but 20 percent lower in the case of LDCs. Thus the imbalance in

terms of gains is partly reversed. However, the qualitative results remain: the increase in exports

by developing countries is 5 times larger under the 50 percent tariff cut than under the 50 percent

domestic support cut. Similarly, for LDCs the increase in exports under the 50 percent tariff cut

is 2 times larger than under the domestic support cut. The welfare gains for developing countries

are positive in the case of tariffs, whereas they suffer welfare losses when domestic support is

cut. For LDCs the welfare increase is 50 percent higher under the tariff cut.

As noted earlier, we cannot empirically identify the elasticity of domestic support on

import demand and export supply separately, but only its sum. To test the sensitivity of our

assumption that the two are equal, we assume that each in turn is zero and that the coefficient

identifies the other one. The estimated changes in export revenue, imports and welfare of a 50

percent tariff cut are not affected by these modifications (as import demand and export supply

are re-calibrated accordingly). In the case of a 50 percent cut in domestic support, the increase in

exports by developing countries is 30 percent higher when we assume that the domestic support

elasticity of export supply is zero and 80 percent lower when we assume that the domestic

18

support elasticity of import demand is zero. In terms of developing countries’ welfare, the loss is

22 percent lower when the elasticity of export supply is zero and 25 percent higher when the

elasticity of import demand is zero. However, the qualitative results remain the same. In the case

of LDCs, the estimated change in exports is only marginally affected under both scenarios.

We also ran a scenario where the 50 percent cut in tariffs and domestic support is

undertaken only by OECD countries. In the case of domestic support, the increase in exports of

developing countries is only 3 percent lower, which suggests that for non-LDC developing

countries almost all the action from the reduction in domestic support comes from actions by the

OECD. However, the increase in exports is 25 percent lower for LDCs. This suggests that

domestic support in other developing countries affect LDC exports to a larger extent than other

developing countries. This is also the case for tariff cuts. When OECD countries cut their tariffs

by 50 percent, the increase in LDC exports is only 30 percent of the increase in exports when all

WTO members reduce their tariffs by 50 percent. For other developing countries, the increase in

exports under an OECD tariff cut is only half of the $4.2 billion generated if all WTO members

reduce their tariffs by 50 percent. These results illustrate the importance of more general

liberalization of trade in the commodities concerned.

6 Conclusions

As is the case for tariff peaks—see Hoekman, Ng and Olarreaga (2002)—we find that LDCs are

disproportionately affected by agricultural support policies. Reducing such support is therefore

important. However, tariffs matter a lot more than subsidies in terms of their impact on world

prices. The positive welfare effect of reducing tariffs on products that are also affected by

agricultural support is a multiple of what can be achieved from an equivalent percentage cut in

domestic support only—tariff reductions generate welfare gains that are a multiple of what can

be obtained from reductions in support policies. This not only reflects the high tariff peaks in

OECD countries, but the fact that developing countries use tariffs to protect domestic production.

These countries generally have low levels of domestic support, reflecting both budget constraints

and a more neutral policy stance in terms of supporting this sector of the economy.

Our analysis suggests the primary focus of attention should therefore be on reducing

border protection in both OECD and developing countries. The negotiating challenge is how to

achieve this. For developing countries tariffs are an important—indeed often the only—

instrument of intervention that they have available to respond to the effects of OECD subsidy

19

policies. An important dimension of agricultural support policies that has been ignored in this

paper—the impact on price volatility—plays a major role here (Valdes and Foster, 2002). Tariff

protection can shelter farmers from import surges in periods where world prices drop

significantly. Whatever the source of the exogenous shock that drives prices down, much of the

adjustment may fall disproportionately on residual (non-OECD) markets because support

policies shelter OECD farmers from the shock. Unilateral liberalization of agricultural trade in

countries such as India proved to be politically unsustainable as farmers were subjected to large

world price swings and import surges of subsidized commodities (Gulati and Narayanan, 2002).

Further agricultural trade liberalization in developing countries may be significantly impeded in

an environment that is characterized by continued large-scale support for OECD farmers.

Substantial reduction in OECD agricultural support policies is therefore important not only

because it generates direct benefits for the many developing economies that are net exporters, it

is critical to create the political support to induce (allow) developing country governments to

continue to pursue welfare improving domestic agricultural trade policy reforms. Thus,

reductions in production subsidies in OECD countries are necessary, although not sufficient, for

developing countries to reap significant gains from the current WTO negotiations on agriculture.

At the same time, as noted by Anderson (2002), if OECD members were to move on the subsidy

front, it is important that developing countries reduce protection. Without own liberalization the

negative welfare effects for countries that experience terms of trade losses would likely be

greater.

The fact that our simulations suggest that a number of countries are predicted to lose

from reforms suggests liberalization and removal of domestic support should be accompanied by

compensation mechanisms, which could include additional ‘aid for trade’ (Hoekman, 2002). Any

negotiated reforms will only be implemented gradually, allowing for measures to support

adjustment. Such measures should include actions that improve the functioning of input,

downstream and factor markets to support efforts by farmers to expand output in response to a

rise in prices (Anderson and Hoekman, 2000). Measures to reduce costs for farmers are

particularly important. Examples include action to improve the efficiency of services—finance,

insurance, transport, storage, packaging, etc. The cost-increasing effect of inefficient services can

be substantial—as illustrated in recent research on transport services (Fink et al. 2002; Francois

and Wooton, 2001). Indeed, if such accompanying measures are taken, the resulting supply

20

response may cause some countries to shift from net importer to net exporter status, attenuating

the magnitude of the negative effects estimated above (Anderson, 2002).

Finally, it is important to bear in mind that our analysis has been limited to only a few—

the subsidized—commodities. The Doha negotiations span all trade, including non-subsidized

agricultural products and manufactures. The overall welfare numbers generated by our analysis

are therefore not particularly relevant, except to indicate that the countries that lose from reforms

that affect the subsidized sub-set of agricultural products will need to identify other areas in

which they can generate offsetting gains. In principle this should be feasible given the large

negotiation set that was established in Doha.

21

References

Anderson, Kym. 2002. “Trade Liberalization, Agriculture and Poverty in Low Income Countries,” presented at the TIPS Annual Forum (September). See www.tips.org.za.

Anderson, Kym and Bernard Hoekman. 2000. “Developing Country Agriculture and the New Trade Agenda,” Economic Development and Cultural Change 49: 171-90.

Beghin, John, David Roland-Holst and Dominique van der Mensbrugghe (2002), “How will Agricultural Trade Reforms in High-Income Countries Affect the Trading Relationships of Developing Countries?, World Bank, mimeo.

Brenton, Paul and Miriam Manchin (2002), “Making EU trade agreements work: the role of rules of origin”, Center for European Policy Studies Discussion Paper 183 (March).

Dimaranan, Betina, Thomas Hertel and Roman Keeney. 2002. “OECD Domestic Support and the Developing Countries,” Purdue University, mimeo.

Fink, C., A. Mattoo and I. Neagu. 2002. “Trade in International Maritime Services: How Does Policy Matter,” World Bank Economic Review.

Fontagné, Lional, J.L. Guérin and S. Jean (2002), “Multilateral Trade Liberalization: Scena rios for the New Round and Assessment,” CEPII, Paris, mimeo.

Francois, J. and I. Wooton. 2001. Trade in International Transport Services: The Role of Competition,” Review of International Economics 9:249-61.

de Gorter, Harry (2002), “The AMS and Domestic Support in WTO Trade Negotiations on Agriculture: issues and suggestions for new rules”, The World Bank, mimeo.

Gulati, Ashok and Sudha Narayanan (2002), “Managing Import Competition When Developing Countries Liberalize Trade: The Indian Experience,” IFPRI, mimeo.

Hertel, Thomas. 1989. “Negotiating Reductions in Agricultural Support: Implications of Technology and Factor Mobility,” American Journal of Agricultural Economics, August, pp. 559-73.

Hoekman, Bernard (2002) “Strengthening the Global Trade Architecture for Development: The Post-Doha Agenda,” World Trade Review 1:1, 23-45.

Hoekman, Bernard and Michel Kostecki (2001), The Political Economy of the World Trading System: The WTO and Beyond. Oxford: Oxford University Press.

Hoekman, Bernard, Francis Ng and Marcelo Olarreaga (2002), “Eliminating Excessive Tariffs in the QUAD and Least Developed Country Exports”, World Bank Economic Review 16 (1) 1-21.

Mattoo, Aaditya, Devesh Roy, and Arvind Subramanian (2002), “The Africa Growth and Opportunity Act and Rules of Origin: Generosity Undermined?,” IMF/World Bank, mimeo (http://www.worldbank.org/trade).

OECD (2000), “Post Uruguay Rounds tariff regimes: achievements and outlook,” OECD: Paris. Rae, Allan and Anna Strutt. 2002. “The Current Round of Agricultural Trade Negotiations: Why

Bother about Domestic Support?,” presented at the 5th annual conference on global economic analysis, Taipei, 5-7 June.

Schiff, M. and A. Valdés (1998), Agriculture and the Macroeconomy,” Policy Research Working Paper 1967, World Bank.

Stawowy, Wojciech (2001), “Calculation of ad-valorem equivalents of non-ad-valorem tariffs: methodology notes”, UNCTAD, Geneva, mimeo.

22

Valdés, Alberto and William Foster (2002), “On the Management of Price Risk in the Context of Trade Reform in LDCs,” mimeo.

Zietz, Joachim and Alberto Valdés (1986), “The potential benefits to LDCs of Trade Liberalization in Beef and Sugar by Industrialized Countries”, Weltwirtschaftliches Archiv 122 (1), 94-112.

23

Table 1: Total Domestic Support Notifications to WTO by Income Country Group, 1995-98 ($ million)

Green box (exempt) /a

Domestic support /b Total (DS1-DS9) /a/b Country/Group /c 1995 1996 1997 1998 1995 1996 1997 1998 1995 1996 1997 1998

Industrial Countries (23) 145069 139650 77971 4730 119094 114118 37725 3980 264163 253767 115696 8711of which: Canada 1529 1463 1482 5306 3011 6769 European Union (15) 51833 55360 66743 65905 118577 121265 Japan 33691 25905 21919 37686 30952 26544 71377 56858 48464 Norway 1771 1762 1562 1560 1559 1645 1505 1459 3329 3407 3068 3019Switzerland 2299 2404 2121 2191 3625 2964 2374 2257 5924 5368 4494 4448United States 53071 51825 51249 7699 7074 7050 0 60770 58899 58299

Developing Countries (81) 21484 18468 17439 7208 16418 7269 13279 10971 37902 25737 30718 18179of which: Brazil 5241 2872 3739 295 363 307 5536 3235 4046 Colombia 450 719 426 58 4 14 508 723 441 Israel 292 414 338 533 559 554 825 973 892 Korea 5200 6481 6133 3858 3057 2872 2711 1674 8257 9353 8844 5532Poland 436 549 878 851 254 227 292 302 691 776 1170 1154South Africa 763 525 544 617 654 542 1380 1179 1086 Thailand 1568 2106 1738 1160 633 510 534 397 2202 2616 2272 1556Venezuela 730 657 675 3064 794 1054 3793 1450 1730

Least Developed Countries (30) 12 112 3 61 0 0 0 0 12 112 3 61 All countries 166565 158230 95413 11999 135512 121387 51004 14951 302077 279617 146417 26950

Memo: As % of total share Industrial Countries (23) 87.1 88.3 81.7 39.4 87.9 94.0 74.0 26.6 87.4 90.8 79.0 32.3Developing Countries (81) 12.9 11.7 18.3 60.1 12.1 6.0 26.0 73.4 12.5 9.2 21.0 67.5Least Developed Countries (30) 0.0 0.1 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2

Notes: /a Green box, measures that are exempt for developing countries and policies covered by production-limiting programs (WTO categories DS1,DS2,DS3). /b Comprises WTO categories DS4 to DS9—includes price support. See text for discussion and description. /c Number of countries reported in the parentheses. A total of 120 countries notified to WTO during 1995-98 Source: Based on WTO document G/AG/NG/S/1.

24

Table 2: Commitments and Average Direct Domestic Support Levels, 1995-98

Direct Support ($ mil) As % of Total (in %) HS-2 Product Commitment 1995-98Commitment 1995-98

01 Live animals. 250 63 0.1 0.1 02 Meat and edible meat offal 60155 14907 22.3 18.5 04 Dairy prod; birds' eggs; honey 39372 11557 14.6 14.3 06 Live tree & other plant; bulb, cut flowers 0 14 0.0 0.0 07 Edible vegetables and roots & tubers 10326 3975 3.8 4.9 08 Edible fruit and nuts; melons 7879 3474 2.9 4.3 09 Coffee, tea, mat and spices 1272 50 0.5 0.1 10 Cereals. 104109 27953 38.5 34.6 11 Milled products; malt; starches 421 142 0.2 0.2 12 Oil seed, oleaginous fruits 8577 447 3.2 0.6 13 Lac; gums, resins & other vegetables 0 0 0.0 0.0 15 Animal/vegetable fats & oils & prod 1899 1050 0.7 1.3 17 Sugars and sugar confectionery 12370 5304 4.6 6.6 18 Cocoa and cocoa preparations 16 0 0.0 0.0 20 Prep of vegetable, fruit, nuts prod 892 529 0.3 0.7 21 Miscellaneous edible preparations 0 0 0.0 0.0 22 Beverages, spirits and vinegar 4306 1172 1.6 1.5 23 Residues & waste from food industry 382 192 0.1 0.2 24 Tobacco and manufactured 2662 735 1.0 0.9 50 Silk. 416 14 0.2 0.0 51 Wool, fine/coarse animal hair nest 124 17 0.0 0.0 52 Cotton. 3411 655 1.3 0.8 53 Other vegetable textile fibers & yarns 34 71 0.0 0.1 98 Non-product specific 11276 8392 4.2 10.4 Total Above Agricultural Products 270151 80714 100.0 100.0

Note: Direct domestic support is defined as the sum of WTO DS4-9 categories. See text. Source: Based on WTO document G/AG/NG/S/1.

25

Table 3: Average MFN Tariff on Products Benefiting from Domestic Support (including ad valorem equivalent of specific tariffs)

MFN Applied Tariff Maximum Rate Countries Average 1995-98 (%) Average 1995-98 (%) Developed Countries Australia 1 7 Canada 30 1403 EEC15 22 219 Iceland 9 61 Japan 51 865 New Zealand 1 10 Norway 19 555 United States 14 121 Developing Countries Albania 14 30 Algeria 24 45 Antigua and Bar 27 40 Argentina 9 21 Bahrain 7 120 Barbados 22 40 Belize 24 40 Bolivia 10 10 Brazil 9 33 Cameroon 23 30 Chile 11 11 China 28 114 Colombia 14 20 Congo, Rep. 21 30 Costa Rica 13 103 Cote d'Ivoire 17 35 Cuba 9 30 Czech Republic 11 124 Dominica 22 40 Dominican Republic 17 35 Ecuador 13 20 Egypt, Arab Rep 31 1050 El Salvador 13 25 Gabon 23 30 Ghana 19 25 Grenada 20 40 Guatemala 12 20 Guyana 25 100 Honduras 14 30 Hungary 30 85 India 28 185 Indonesia 13 104 Iran, Islamic R 3 15 Israel 4 22 Jamaica 25 40 Jordan 23 180 Kenya 22 50 Korea, Rep. 46 284 Latvia 10 45 Lithuania 8 71 Malaysia 8 257 Malta 3 40 Mauritius 20 80 Mexico 15 171 Morocco 45 362 Nicaragua 8 38 Nigeria 27 75

26

MFN Applied Tariff Maximum Rate Countries Average 1995-98 (%) Average 1995-98 (%) Oman 2 5 Pakistan 36 70 Panama 11 50 Papua New Guinea 38 85 Paraguay 9 25 Peru 16 25 Philippines 22 58 Poland 14 44 Romania 21 144 Russian Federation 9 25 Rwanda 25 100 Saudi Arabia 11 65 Slovenia 9 49 South Africa 7 55 Sri Lanka 33 60 St. Kitts and N 21 40 St. Lucia 22 40 Suriname 22 50 Taiwan, China 18 50 Thailand 41 65 Trinidad and Tobago 20 40 Tunisia 33 43 Turkey 28 145 Uruguay 10 24 Venezuela 13 20 Zimbabwe 26 68 Least Developed Countries Bangladesh 40 300 Burkina Faso 21 37 Central African 20 30 Chad 22 30 Madagascar 7.5 20 Malawi 18 45 Maldives 16 50 Mali 19 30 Mozambique 15 35 Solomon Islands 40 100 Sudan 8 30 Tanzania 29 40 Uganda 13 36 Zambia 17 25 Memo: All Above Countries 18 1403 Industrial Countries 19 1403 Developing Countries (non-LDC) 17 1050 Least Developed Countries 20 300

Note: Countries with zero tariffs not reported (Brunei, Estonia, Hong Kong, Kyrgyz, Rep. Singapore) Source: UNCTAD TRAINS tariff data (through WITS), OECD (2000) and Stawowy (2001).

27

Table 4: Average MFN Tariff on Products with Domestic Support

Average Maximum HS-2 Product 1995-98 (%) 1995-98 (%)

01 Live animals. 11.6 555.0 02 Meat and edible meat offal 21.0 361.5 04 Dairy prod; birds' eggs; honey 29.4 349.5 06 Live tree & other plant; bulb, cut flowers 16.2 249.0 07 Edible vegetables and roots & tubers 24.0 865.4 08 Edible fruit and nuts; melons 20.0 238.9 09 Coffee, tea, mat and spices 16.7 559.3 10 Cereals. 21.8 719.1 11 Milled products; malt; starches 31.1 1402.8 12 Oil seed, oleaginous fruits 11.2 686.0 13 Lac; gums, resins & other vegetables 10.8 65.0 15 Animal/vegetable fats & oils & prod 15.3 188.0 17 Sugars and sugar confectionery 26.6 209.0 18 Cocoa and cocoa preparations 9.0 55.0 20 Prep of vegetable, fruit, nuts prod 23.0 162.8 21 Miscellaneous edible preparations 32.1 302.4 22 Beverages, spirits and vinegar 36.7 1050.0 23 Residues & waste from food industry 7.1 45.0 24 Tobacco and manufactured 20.1 257.3 50 Silk. 23.4 235.8 51 Wool, fine/coarse animal hair 6.3 54.9 52 Cotton. 5.2 35.3 53 Other vegetable textile fibers & yarns 5.9 52.5 Total (all items with positive domestic support) 18.4 1402 Memo: All Agricultural Products 19.8 1772 Source: UNCTAD TRAINS tariff data (through WITS), OECD (2000) and Stawowy (2001).

28

Table 5: Trade in Domestically Supported Agricultural Products by Country, 1995-98

Country (No. of countries)

Exports of goods supported by WTO

members ($m)

Ave 1995-98

Imports of goods

supported in WTO

members($m) Ave 1995-98

Exports of goods

supported by WTO members

as % of All Exports

Imports of goods supported in WTO

members as % of

All Imports Albania 24 74 8.8 8.2 Algeria 5 1902 0.0 20.0 Angola 12 139 0.3 7.2 Antigua and Barbuda 3 9 6.0 2.8 Argentina 6251 603 25.6 2.3 Australia 9384 843 17.0 1.4 Bahrain 2 71 0.1 3.7 Bangladesh 90 805 2.2 12.7 Barbados 46 40 21.9 5.9 Belize 70 16 46.6 5.9 Benin 230 57 84.7 5.9 Bolivia 137 95 11.3 5.2 Brazil 6494 3968 13.1 6.7 Brunei 1 56 0.0 1.8 Bulgaria 333 276 6.9 5.4 Burkina Faso 130 35 75.5 7.9 Burundi 76 19 72.8 10.9 Cameroon 422 114 24.7 8.6 Canada 7023 3918 3.4 2.1 Central African Rep. 48 5 24.8 4.4 Chad 109 5 82.5 3.5 Chile 2225 542 14.2 3.2 China 3243 5471 1.9 4.0 Colombia 3460 1031 32.0 7.2 Comoros 0 13 0.1 24.3 Congo, Dem. Rep 147 76 10.6 8.6 Congo, Rep. 21 35 1.1 3.9 Costa Rica 1361 257 37.5 5.9 Cote d'Ivoire 1835 299 48.7 11.0 Croatia 101 411 2.2 5.0 Cuba 745 337 50.7 13.4 Cyprus 115 160 24.5 4.2 Czech Republic 443 1001 1.9 3.6 Djibouti 3 34 9.5 9.9 Dominica 21 7 57.7 7.1 Dominican Repub. 469 414 10.2 7.4 Ecuador 1457 258 31.2 5.7 EEC15 17375 38075 2.2 4.9 Egypt, Arab Rep 387 2319 11.0 17.1 El Salvador 485 236 42.0 8.3 Estonia 158 237 6.3 6.3 Fiji 222 46 37.9 6.5 Gabon 2 43 0.1 4.9 Gambia, The 2 41 11.0 17.5 Ghana 494 115 32.4 4.7 Grenada 4 12 14.5 7.2 Guatemala 1081 271 48.6 7.2 Guinea 38 99 7.8 19.1 Guinea-Bissau 31 4 39.8 4.2

29

Country (No. of countries)

Exports of goods supported by WTO

members ($m)

Ave 1995-98

Imports of goods

supported in WTO

members($m) Ave 1995-98

Exports of goods

supported by WTO members

as % of All Exports

Imports of goods supported in WTO

members as % of

All Imports Guyana 182 27 33.1 6.7 Haiti 29 127 12.2 14.9 Honduras 385 194 43.9 9.0 Hong Kong, China 22 2964 0.1 1.5 Hungary 955 455 5.6 2.3 Iceland 148 54 7.9 2.6 India 2782 964 8.4 2.4 Indonesia 1394 3396 2.8 8.9 Iran, Islamic Rep. 163 1102 1.0 10.3 Israel 876 938 4.1 3.3 Jamaica 229 136 12.1 5.5 Japan 312 15850 0.1 4.9 Jordan 53 397 6.2 12.3 Kazakhstan 0 0 0.0 0.0 Kenya 790 210 48.7 8.4 Korea, Rep. 400 4727 0.3 3.6 Kuwait 4 277 0.0 4.0 Kyrgyz Republic 83 24 24.1 4.7 Latvia 32 143 2.0 5.7 Lithuania 227 244 6.7 5.0 Macao 6 51 0.3 2.5 Madagascar 77 45 26.6 7.8 Malawi 361 17 75.7 4.4 Malaysia 354 2457 0.5 3.4 Maldives 1 26 2.1 8.3 Mali 255 35 84.5 5.8 Malta 20 81 1.2 3.0 Mauritania 4 72 0.7 13.8 Mauritius 401 185 24.6 8.5 Mexico 3066 4317 3.0 4.3 Mongolia 48 10 12.0 2.2 Morocco 481 1204 9.0 13.8 Mozambique 0 0 0.0 0.0 Myanmar 284 27 23.6 1.0 New Zealand 3194 412 24.1 3.0 Nicaragua 239 110 40.0 8.7 Niger 34 48 17.2 12.9 Nigeria 277 431 1.8 7.5 Norway 116 980 0.3 2.8 Oman 45 281 0.7 5.8 Pakistan 536 543 7.0 6.7 Panama 244 121 38.8 4.1 Papua New Guinea 351 36 15.1 2.6 Paraguay 568 109 55.1 3.5 Peru 1144 778 19.3 9.6 Philippines 1468 1388 5.6 4.5 Poland 672 1917 2.7 4.9 Qatar 1 64 0.0 2.3 Romania 403 424 4.9 3.8 Russian Federation 931 3227 1.4 6.9 Rwanda 42 40 59.0 18.2

30

Country (No. of countries)

Exports of goods supported by WTO

members ($m)

Ave 1995-98

Imports of goods

supported in WTO

members($m) Ave 1995-98

Exports of goods

supported by WTO members

as % of All Exports

Imports of goods supported in WTO

members as % of

All Imports Saudi Arabia 77 2045 0.1 6.3 Senegal 44 221 7.6 16.1 Sierra Leone 12 17 6.6 8.7 Singapore 677 1449 0.6 1.2 Slovak Republic 197 332 2.1 3.0 Slovenia 79 343 0.9 3.6 Solomon Islands 20 2 9.1 1.7 South Africa 1496 902 6.4 3.2 Sri Lanka 81 405 2.1 9.1 St. Kitts and Nevis 14 6 77.5 5.6 St. Lucia 45 17 63.8 5.3 St. Vincent and Grenadines 28 13 57.3 10.5 Sudan 290 127 60.1 8.6 Suriname 46 23 11.6 5.5 Switzerland 398 2496 0.5 3.2 Taiwan 247 3820 0.2 3.6 Tanzania 448 63 67.8 5.0 Thailand 3938 1715 7.0 2.8 Togo 103 40 42.5 6.3 Trinidad and Tobago 50 160 2.1 6.4 Tunisia 223 553 4.0 6.9 Turkey 2565 2147 10.5 5.0 Uganda 349 73 63.3 7.5 United Arab Emirates 225 782 1.0 3.1 United States 31450 15475 5.2 1.8 Uruguay 575 211 23.0 6.2 Venezuela 171 938 0.8 8.0 Zambia 76 30 8.1 4.0 Zimbabwe 1057 61 59.3 3.0 Memo: All above countries (143) 136483 151021 3.6 3.7 Industrial Countries (23) 69400 78103 3.1 3.3 Developing Countries (90) 63781 70616 4.2 4.2 Least Developed Countries (30) 3302 2302 17.8 8.9

Source: Based on UN COMTRADE Statistics.

31

Table 6: Estimates of price and domestic support elasticities a

(1) (2) (3) (4)

)log( GDP

0.26 (0.03)**

0.24 (0.03)**

0.26 (0.03)**

0.24 (0.03)**

)log( Pop -0.35

(0.03)**

-0.33 (0.03)**

-0.35 (0.03)**

-0.33 (0.04)**

)1log( t+

( )dε− -1.36

(0.27)**

-1.46 (0.31)**

-1.37 (0.27)**

-1.42 (0.31)**

)1log( τ+

( )sd εε −− -1.17

(0.08)**

-1.17 (0.08)**

-1.17 (0.08)**

-1.17 (0.08)**

)log( 94−DSs

( )sd λλ +−

-0.10 (0.02)**

-0.10 (0.03)**

)log( 31−DSs ( )sd λλ +−

-0.05 (0.02)**

-0.00 (0.03)

)log( 9431 −− + DSDS ss ( )sd λλ +−

-0.06 (0.02)**

Product dummies 2adjR

# of observations # HS 6-digit lines

Yes 0.136 7610 158

Yes 0.135 7610 158

Yes 0.136 7610 158

Yes 0.135 7610 158

a Estimation procedure is OLS. Standard errors in parenthesis are White Robust. “**” Significant at the 1 percent level. “*” significant at the 5 percent level.

32

Table 7: Estimates of price and domestic support elasticities by group of productsa

(1)

HS 01 to 04 Animal

products

(2) HS 06 to 09 Vegetables, fruits&nuts

(3) HS 10 to 14 Cereals&

other grains

(4) HS 15 to 24

Food process. products

(5) HS 50 to 53 Silk, cotton

&other fibers

)log( GDP

-0.21 (0.08)**

0.51 (0.05)**

0.10 (0.06)

0.18 (0.06)**

0.56 (0.16)**

)log( Pop 0.14 (0.09)

-0.67 (0.05)**

-0.18 (0.07)*

-0.20 (0.07)**

-0.19 (0.17)

)1log( t+ ( )dε−

-0.70 (0.51)

-2.16 (0.53)**

0.06 (0.62)

-2.35 (0.53)**

-0.44 (2.74)

)1log( τ+ ( )sd εε −−

-0.86 (0.18)**

-1.12 (0.13)**

-1.25 (0.14)**

-1.44 (0.20)**

-0.98 (0.42)*

)log( 94−DSs ( )sd λλ +−

-0.07 (0.05)

-0.11 (0.04)*

-0.07 (0.04)

-0.16 (0.05)**

-0.11 (0.10)

Product dummies 2adjR

# of observations # HS 6-dig lines

Yes 0.104 1128 28

Yes 0.164 3028 55

Yes 0.164 1698 38

Yes 0.109 1448 27

Yes 0.09 308 10

a Estimation using Seemingly Unrelated Regression procedure. Group specific elasticities estimated using the information in the whole sample, letting the elasticities vary by group of products. Standard errors in parenthesis are White Robust. “**” significant at the 1 percent level; “*” significant at the 5 percent level.

33

Table 8: Impact of a 50 percent cut in tariffs and domestic support (DS) (158 products)

Tariff cut Cut in DS Change in welfare Country group

Change in exports

($ mil)

Change in imports

($ mil)

Change in exports

($ mil)

Change in imports

($ mil)

Tariff cut

($ mil)

DS cut

($ mil) Industrial Countries 3,262 7677 314 121 14,464 541 Developing Countries 4,146 4136 504 -92 2,293 -273 Least Developed Countries 116 118 64 -4 52 36

(percent) (percent) (percent) (percent) ($ per capita) ($per capita) Industrial Countries 4.7 9.8 0.5 0.2 18.37 0.69 Developing Countries 6.7 6.0 0.8 -0.1 0.56 -0.07 Least Developed Countries 3.7 5.3 2.0 -0.2 0.12 0.08

34

Figure 1: Changes in Exports by Country (50 % tariff cut vs. 50 % cut in domestic support)

Ch

an

ge

in

Exp

ort

s (

T=

-50

%)

Change in Exports (DS=-50%)-2.21439 3.90456

0

24.2375

alb

dza

ago

atg

argbhrbgd

brb

blz

ben

bol

brabrn

bgr

bfa

bdi

cmr

caf

tcd

chlchncol

com

zar

cog

cri

civ

hrv

cub

cyp cze

dji

dma

dom

ecu

egy

slv

est

fji

gab

gmb

gha

grd

gtm

gingnb

guy

hti

hnd

hkg

hunindidn

irn

isr

jam

jorken

kor

kwtkgz

lvaltu

mac

mdg

mwimys

mdv

mli

mlt

mrt

mus

mex

mng

mar

mmrnic

ner

nga

omnpak

pan

pngpryper

phl

pol

qatrom

rus

rwa

sau

sensle

sgpsvksvn

slb

zaf lka

kna

lca

vct

sdn

suroan

tza

tha

tgo

tto

tun

tur

uga

areury

ven

zmb

zwe

Figure 2: Changes in Imports by Country (50 % tariff cut vs. 50 % cut in domestic support)

Ch

an

ge

in

Im

po

rts (

T=

-50

%)

Change Imports (DS=-50%)-.566081 1.62701

-2.82001

18.1081

alb

dza

ago

atg

arg

bhr

bgd

brb

blz

ben

bol bra

brn

bgr

bfa

bdi

cmr

caf

tcd

chl

chn

col

comzar

cog

cri

civ

hrv

cub

cyp

cze

dji

dma

dom

ecu

egy

slv

est

fji

gab

gmb

gha

grd

gtm

gingnb

guy

hti

hnd

hkg

hun

ind

idn

irn

isr

jam

jorken

kwt

kgz

lva

ltu

mac

mdg

mwi

mys

mdv

mli

mlt mrt

mus

mex

mng

mar

mmr

nic

nernga

omn

pak

pan

png

pry

per

phl

pol

qat

rom

rus

rwasau

sensle

sgp

svk

svn

slb

zaf

lka

kna

lca

vct

sdn

sur

oan

tza

tha

tgo

tto

tun

tur

uga

are

ury

ven

zmb

zwe

45o

45o

35

Figure 3: Changes in the Terms of Trade (50% tariff cut vs. 50% cut in domestic support)

Ch

an

ge

in

To

T (

T=

-50

%)

Change in ToT (DS=-50%)-7.27798 3.69431

-7.27798

7.3641

alb

dza ago

atg

arg

bhr

bgd

brb

blz

ben

bol

bra

brn

bgrbfa

bdi

cmrcaf tcd

chl

chn

col

com

zarcog

cri

civ

hrv

cub

cypcze

dji

dma

dom

ecu

egy

slvest

fji

gab

gmb

gha

grd

gtm

gin

gnb

guy

hti

hnd

hkg

hun

ind

idn

irn

isr

jam

jor

ken

kor

kwt

kgz

lva

ltu

mac

mdg

mwi

mys

mdv

mli

mlt

mrt

mus

mexmng

mar

mmr

nic

ner

nga

omn

pak

pan

pngpry

per

phl

pol

qat

rom

rus

rwa

sau

senslesgp

svk

svn

slbzaf

lka

kna

lca

vct

sdn

sur

oan

tza

tha

tgo

ttotun

turuga

are

ury

ven

zmb

zwe

Figure 4: Changes in Welfare by Country ($ per capita) (50% tariff cut vs. 50% cut in domestic support)

Ch

an

ge

in

We

lfa

re (

T=

-50

%)

Change in Welfare (DS=-50%)-4.26036 3.00162

-18.2294

34.4165

albdza

agoatg

arg

bhr

bgd

brb

blz

benbolbra

brn

bgrbfabdicmrcaf tcd

chlchn

colzarcog

cri

civhrv

cubcyp

cze dji

dma

dom

ecu

egyslvest

fji

gabgmbgha

grd

gtm

gingnb

guy

htihnd

hkg

hun

indidnirnisr

jam

jorkazkenkwt kgz

lva

ltumacmdg

mwimys

mdv

mlimrt

mus

mex mngmar

mmrnicnernga

omn

pak

pan

png pryperphlpol qatromrusrwa

sau

sensle

sgp

svk

svn

slbzaflka

kna

lca

vct

sdn

sur

oantza

tha

tgo

ttotun

tur uga

are

ury

venzmb

zwe

450

450

36

Annex: Data Sources

All trade data are from UN Comtrade Database (both value figures and unit prices). When

countries did not report trade data to Comtrade we mirror their data using notifications by their

trading partners. Tariffs are drawn from the UNCTAD and WTO as provided in

UNCTAD/World Bank World Integrated Trade Solution (WITS) system. This database does not

include the ad-valorem equivalent of specific tariffs. For ad-valorem equivalents of specific

tariffs we rely on Stawowy (2001) for estimates for Canada, the European Union, Japan and the

United States and OECD (2000) for other OECD countries. In cases where tariff quotas are used,

tariff rates generally comprise the average of in and out of quota tariffs is generally taken,

although in some cases only the out of quota tariff is available. The OECD ad-valorem

equivalents of specific tariffs use exclusively out of quota tariffs. We do not have quota

information, this may bias results some estimates as some import prices may be higher if

exporters benefit from in-quota lower tariffs.

As mentioned in the text, the source of domestic support data is the WTO (document

G/AG/NG/S/1). This data comes in national currency and was transformed into US dollars using

the period average exchange rate reported in the IMF IFS. The product classification in each

country notification is arbitrary and therefore we filter the product classification into the

Harmonized System 6 digit classification. In most cases this can be done through a one-to-one

mapping. In some cases, the domestic support reported covers several 6 digit tariff lines, in

which case the subsidy was distributed across the relevant tariff lines using the share of the

reporting country’s exports as weights. The concordance file is available from the authors on

request.

As exempt subsidies are not product specific, these were also mapped into a product

specific subsidies using as weights the product-specific commitments that each country made in

the Uruguay Round. Non-product specific support is divided evenly into all products exported by

the country concerned. All products shown in notifications to the WTO are included, whether or

not the support is below the de minimis level for the member concerned. Thus, total AMS may

exceed total WTO commitments for a country. GDP (in US dollars) and population data are

drawn from the World Bank’s World Development Indicators database.

37

Appendix Table 1: Impact of tariff and domestic support cuts by group of products

Change in Change in Change in Change in Change in Change in Change in Change in exports imports exports imports exports imports exports imports

with 50 percent

with 50 percent

with 50 percent

with 50 percent

with 50 percent

with 50 percent

with 50 percent

with 50 percent

HS 2 digit tariff cut tariff cut cut in DS cut in DS tariff cut tariff cut cut in DS cut in DSproducts ($'000) ($'000) ($'000) ($'000) (percent) (percent) (percent) (percent)

A. Impact on developing countries (non-LDCs): 01 Live animals. 26116 21278 -916 1035 4.8 2.1 -0.2 0.102 Meat and edible meat offal 31104 40741 4569 2526 4.7 4.4 0.7 0.304 Dairy prod; birds' eggs; honey 157823 338591 25782 32685 8.5 5.7 1.4 0.506 Live tree & other plant; bulb 28293 26664 24664 -2178 2.1 7.3 1.8 -0.607 Edible vegetables and roots 442019 169647 22424 -3387 10.1 6.3 0.5 -0.108 Edible fruit and nuts; melons 1138841 234312 106692 -34114 12.3 4.9 1.2 -0.709 Coffee, tea, mat and spices 110458 116167 -32060 -6439 1.2 7.6 -0.3 -0.410 Cereals. 353031 1739555 126545 -40021 3.9 7.6 1.4 -0.211 Milled products; malt; starches 25671 57062 86 511 9.6 5.8 0.0 0.112 Oil seed, oleaginous fruits; 87943 501554 46149 3421 1.9 7.9 1.0 0.113 Lac; gums, resins & other veg 43 3176 0 1 3.3 4.0 0.0 0.015 Animal/veg fats & oils & prod 195152 122296 6290 -2105 7.3 6.2 0.2 -0.117 Sugars and sugar confectionery 693521 131776 9157 -18079 14.3 4.8 0.2 -0.718 Cocoa and cocoa preparations 15787 22191 93 57 0.6 3.8 0.0 0.020 Prep of vegetable, fruit, nuts 196982 72345 25567 -7897 13.8 9.4 1.8 -1.021 Miscellaneous edible prep. 246069 59568 -117 3008 18.7 2.3 0.0 0.122 Beverages, spirits and vinegar 32659 76229 13423 -5818 4.4 14.0 1.8 -1.123 Residues from food industry 2 61389 -7552 -15189 0.0 4.0 -0.5 -1.024 Tobacco and manufactured 329093 221150 53926 -30836 11.6 10.5 1.9 -1.550 Silk. 6574 503 975 116 23.7 5.3 3.5 1.251 Wool, fine/coarse animal hair 6425 30319 1954 69 1.6 2.7 0.5 0.052 Cotton. 21523 83998 76658 30440 1.1 1.2 3.8 0.453 Other vegetable textile fibers 409 5330 134 189 1.3 4.4 0.4 0.2

B. Impact on LDCs: 01 Live animals. 3593 204 57 6 4.8 1.7 0.1 0.102 Meat and edible meat offal 3188 203 26 2 19.2 1.0 0.2 0.004 Dairy prod; birds' eggs; honey 252 11101 47 489 7.5 4.9 1.4 0.206 Live tree & other plant; bulb 432 68 616 -4 2.4 5.0 3.4 -0.307 Edible vegetables and roots 18426 17035 1035 -108 7.4 12.6 0.4 -0.108 Edible fruit and nuts; melons 1835 8184 417 -191 1.5 24.1 0.3 -0.609 Coffee, tea, mat and spices 7561 973 6809 -61 1.1 2.2 1.0 -0.110 Cereals. 3234 31639 1603 -2247 3.4 3.0 1.7 -0.211 Milled products; malt; starches 38 815 0 -1 9.0 1.9 0.1 0.012 Oil seed, oleaginous fruits; 13423 10066 274 -285 6.0 12.4 0.1 -0.413 Lac; gums, resins & other veg 10 30 0 0 3.3 0.9 0.0 0.015 Animal/veg fats & oils & prod 368 1490 8 -46 7.3 3.3 0.2 -0.117 Sugars and sugar confectionery 14042 17677 1373 -652 14.4 12.6 1.4 -0.518 Cocoa and cocoa preparations 278 0 3 0 0.6 0.0 0.0 0.020 Prep of vegetable, fruit, nuts 99 302 40 -25 7.1 2.4 2.8 -0.221 Miscellaneous edible prep. 379 1814 4 -28 18.7 3.7 0.2 -0.122 Beverages, spirits and vinegar 12 362 5 -18 4.4 3.0 1.8 -0.123 Residues from food industry 0 114 127 -20 0.0 4.8 1.5 -0.824 Tobacco and manufactured 33855 4485 11518 -559 8.9 8.4 3.0 -1.150 Silk. 2 1 0 0 23.7 0.5 3.5 0.151 Wool, fine/coarse animal hair 0 0 1 0 0.8 0.0 1.0 0.052 Cotton. 10712 11036 39801 135 1.1 5.2 3.9 0.153 Other vegetable textile fibers 4223 12 650 0 4.5 1.3 0.7 0.0

38

Appendix Table 2: Impact of a 50 percent cut in tariffs and domestic support (%)

50% tariff cut 50% DS cut Change in terms of trade Change in welfare

Country Change in export rev.

Change in import rev.

Change in export rev.

Change in import rev.

50% tariff cut

50 percent cut in DS

50% tariff cut

($ per capita)

50% cut in DS

($ per capita) Albania 8.5 7.0 1.2 -0.5 -2.8 -0.6 -0.4 -0.1 Algeria 6.5 5.9 1.2 -0.2 -4.5 -1.4 -2.1 -0.9 Angola 1.0 0.0 1.1 0.0 -4.4 -0.7 0.0 0.0 Antigua and Barbuda 6.8 12.6 1.8 -0.3 -1.2 0.2 1.3 0.9 Argentina 4.6 4.5 1.5 -0.5 2.4 1.2 4.9 2.4 Australia 4.8 -3.5 1.0 -0.4 3.1 1.2 17.5 6.5 Bahrain 4.3 2.8 1.2 -0.1 -4.9 -0.6 -4.4 -0.6 Bangladesh 5.0 12.0 0.8 -0.3 -3.2 -1.7 0.0 -0.1 Barbados 14.4 6.7 1.2 -0.3 1.5 -0.3 7.1 -0.5 Belize 16.9 5.1 1.6 -0.1 5.6 0.5 25.5 2.0 Benin 1.2 0.0 3.4 0.0 -0.2 2.4 0.4 1.3 Bolivia 2.4 4.2 2.2 -0.4 -1.0 0.7 -0.2 0.2 Brazil 4.7 4.4 -0.5 0.6 0.0 0.1 0.1 0.1 Brunei 5.5 -1.7 2.5 -0.3 -4.5 -1.1 -7.0 -1.8 Bulgaria 7.1 0.0 1.4 0.0 0.3 -0.2 1.8 0.4 Burkina Faso 3.8 3.5 3.3 -0.2 0.8 2.3 0.3 0.4 Burundi 1.4 0.0 1.0 0.0 -1.1 0.2 0.1 0.1 Cameroon 4.3 6.7 1.5 -0.3 0.4 0.7 0.3 0.3 Canada 3.9 11.3 1.0 -0.5 0.8 0.8 26.9 2.9 Central African Rep. 3.3 4.0 2.3 -0.3 0.8 1.7 0.2 0.3 Chad 1.1 8.1 3.9 0.0 0.8 3.7 0.1 0.6 Chile 4.7 4.9 1.3 -0.3 1.2 0.2 2.6 0.5 China 5.7 18.1 1.2 -0.4 -0.3 -0.9 0.5 0.0 Colombia 5.7 6.9 -0.9 0.7 1.4 0.2 1.8 0.3 Comoros 6.1 0.0 1.0 0.0 -7.3 -1.2 Congo, Dem. Rep 1.5 0.0 1.0 0.0 -1.1 -0.1 0.0 0.0 Congo, Rep. 9.3 5.6 1.3 -0.3 -1.3 -0.3 -0.1 0.0 Costa Rica 14.6 3.8 1.7 -0.5 5.8 0.5 28.4 2.2 Cote d'Ivoire 1.9 7.0 0.6 -0.4 0.1 0.2 0.5 0.3 Croatia 7.2 0.0 1.5 0.0 -2.6 -0.6 1.0 0.3 Cuba 13.8 2.3 1.4 -0.2 3.1 0.0 3.4 0.0 Cyprus 7.1 0.0 0.1 0.0 -0.4 -0.7 5.7 0.4 Czech Republic 7.0 1.7 0.9 -0.4 -0.6 -0.4 -0.3 -0.5 Djibouti 4.9 0.0 0.5 0.0 -3.9 -0.7 0.4 0.0 Dominica 22.6 8.2 2.1 0.1 6.8 0.5 26.9 1.9 Dominican Rep. 10.0 3.2 1.4 -0.6 0.1 -0.2 0.7 -0.2 EEC15 6.9 9.3 -0.3 0.7 -0.8 -0.4 13.9 -0.2 Ecuador 18.5 5.0 2.1 -0.4 7.4 0.7 11.5 1.1 Egypt, Arab Rep 4.6 1.3 2.0 -0.4 -2.6 -1.0 -0.9 -0.4 El Salvador 3.4 4.5 1.0 -0.2 -0.1 -0.2 0.1 -0.2 Estonia 5.9 -1.3 1.2 -0.1 0.1 -0.3 0.6 -0.8 Fiji 13.8 0.0 1.3 0.0 4.0 0.3 15.4 1.4 Gabon 3.0 9.0 1.3 -0.3 -5.0 -0.8 -1.2 -0.2 Gambia, The 8.5 0.0 0.7 0.0 -2.5 -0.5 0.1 0.0 Ghana 1.4 8.1 0.2 -0.4 -0.7 -0.3 -0.1 0.0 Grenada 5.6 6.6 0.5 -0.2 -3.2 -0.6 -3.4 -0.9 Guatemala 8.4 3.7 1.3 -0.2 2.4 0.3 3.6 0.4 Guinea 1.5 0.0 1.2 0.0 -3.4 -0.7 0.1 0.1 Guinea-Bissau 1.1 0.0 0.5 0.0 0.0 0.2 0.2 0.1 Guyana 13.0 5.0 1.3 -0.1 5.5 0.5 16.2 1.3 Haiti 1.2 0.0 0.8 0.0 -5.0 -0.9 0.0 0.0 Honduras 9.8 4.3 1.5 -0.4 1.4 0.2 1.9 0.2 Hungary 5.7 14.3 0.7 -0.3 1.5 0.3 4.0 0.5 Iceland 0.4 3.4 1.4 -0.6 -1.0 0.3 -4.5 2.3 India 5.0 5.7 1.5 0.1 2.2 0.8 0.1 0.0 Indonesia 5.3 0.9 0.8 -0.4 -1.6 -1.4 -0.3 -0.3 Iran, Islamic Rep. 3.6 -1.4 1.6 -0.4 -3.2 -1.1 -0.4 -0.2 Israel 6.3 0.0 0.1 -0.4 -0.1 -0.3 0.3 -1.0 Jamaica 14.4 5.9 1.5 -0.3 2.5 0.0 4.7 0.0 Japan 9.6 18.1 0.7 -0.1 -2.8 -1.4 64.8 -0.5 Jordan 4.9 3.6 0.4 -0.2 -3.8 -1.0 -1.6 -0.4

39

Kenya 4.0 3.9 1.4 -0.5 0.9 0.3 0.3 0.1 Korea, Rep. 7.2 18.1 -1.1 -0.1 -2.4 -1.6 18.0 -1.2 Kuwait 5.8 0.0 0.7 0.0 -5.2 -0.9 0.1 0.0 Kyrgyz Republic 6.8 -2.8 2.1 -0.2 1.5 0.9 0.6 0.3 Latvia 9.6 -0.6 1.2 -0.5 -2.5 -0.6 -1.3 -0.4 Lithuania 9.1 1.3 2.1 -0.3 0.8 0.2 1.8 0.3 Macao 4.3 0.0 0.4 0.0 -3.5 -0.6 0.6 0.1 Madagascar 2.5 1.0 0.9 -0.4 -1.3 -0.1 -0.1 0.0 Malawi 8.4 5.0 2.9 -0.3 3.7 1.3 1.5 0.5 Malaysia 7.9 1.2 0.6 -0.3 -3.0 -1.1 0.2 -1.5 Maldives 0.0 6.3 1.5 -0.2 -5.3 -0.8 -4.8 -0.8 Mali 1.2 3.1 3.8 -0.1 0.4 3.3 0.1 1.0 Malta 16.0 -0.4 0.2 -0.5 -2.1 -0.9 Mauritania 2.3 0.0 1.8 0.0 -3.4 -1.1 0.0 0.0 Mauritius 13.9 6.2 1.4 -0.2 3.2 0.0 19.5 0.1 Mexico 5.1 8.4 0.9 0.5 -0.5 -0.9 0.6 -0.5 Mongolia 1.3 0.0 1.1 0.0 0.1 0.6 0.3 0.2 Morocco 5.5 15.7 1.2 -0.3 -1.8 -0.9 2.1 -0.5 Myanmar 7.1 0.0 0.5 0.0 3.7 0.3 0.3 0.0 New Zealand 6.3 -4.5 1.0 -0.7 4.4 0.7 42.7 6.5 Nicaragua 6.4 2.9 1.2 -0.3 0.7 0.1 0.7 0.1 Niger 5.8 0.0 0.3 0.0 -1.8 -0.9 0.1 0.0 Nigeria 1.0 0.7 0.5 0.0 -2.6 -0.8 0.0 0.0 Norway 5.0 3.0 1.0 -0.6 -2.5 -0.8 1.5 -1.6 Oman 5.7 -0.3 1.0 -0.4 -3.5 -0.9 -4.6 -1.2 Pakistan 4.8 4.6 2.1 -0.2 0.6 0.4 0.1 0.0 Panama 19.4 3.4 2.0 -0.4 5.2 0.3 7.9 0.4 Papua New Guinea 1.5 9.9 0.6 -0.2 0.3 0.2 0.5 0.2 Paraguay 0.9 4.0 2.8 -0.5 -0.2 2.2 -0.1 3.0 Peru 1.0 7.7 -2.2 1.6 -1.3 -0.3 -0.7 -0.1 Philippines 12.8 10.6 0.9 -0.3 0.6 -0.6 0.6 -0.2 Poland 8.7 5.3 1.0 -0.5 -0.9 -0.5 -0.3 -0.3 Qatar 4.6 0.0 0.6 0.0 -4.8 -0.5 0.1 0.0 Romania 5.2 8.1 1.2 -0.5 -0.7 -0.2 0.1 0.0 Russian Fed. 4.1 1.1 2.1 -0.5 -2.9 -0.1 -0.4 0.0 Rwanda 1.2 2.5 1.0 0.0 -1.4 -0.2 0.0 0.0 Saudi Arabia 4.2 2.0 1.4 -0.3 -4.8 -1.2 -4.1 -1.1 Senegal 2.6 0.0 2.8 0.0 -2.5 -0.7 0.1 0.1 Sierra Leone 1.7 0.0 0.8 0.0 -2.1 -0.4 0.0 0.0 Singapore 6.6 -2.7 0.9 -0.4 -2.0 -0.4 -10.3 -2.2 Slovak Republic 6.4 0.0 0.8 0.0 -0.6 -0.2 2.0 0.4 Slovenia 7.1 2.5 1.2 -0.2 -2.3 -0.6 -3.1 -0.6 Solomon Islands 1.6 14.2 0.0 -0.1 0.3 0.0 0.5 0.0 South Africa 6.5 -0.2 1.3 0.5 0.6 0.1 0.5 0.1 Sri Lanka 6.1 15.0 1.9 -0.3 -3.5 -0.7 -0.2 -0.1 St. Kitts and Nevis 14.3 13.1 1.4 -0.3 2.8 0.3 18.7 1.6 St. Lucia 24.2 10.2 2.3 -0.2 7.1 0.6 34.4 2.8 St. Vincent/Grenadines 20.1 5.7 2.1 -0.2 3.4 0.2 19.0 1.1 Sudan 5.7 2.0 1.3 -0.4 2.2 0.5 0.4 0.1 Suriname 10.7 5.6 1.0 -0.2 3.9 0.3 10.3 0.7 Taiwan 10.4 4.5 0.9 -0.4 -1.7 -1.8 -1.4 -3.2 Tanzania 3.0 13.3 2.0 -0.5 1.0 1.3 0.2 0.2 Thailand 12.4 6.4 0.6 0.0 4.2 0.3 4.8 0.3 Togo 1.0 0.0 2.9 0.0 -0.6 1.7 0.2 0.7 Trinidad and Tobago 11.2 5.4 1.2 -0.3 -2.1 -0.8 -2.3 -1.4 Tunisia 1.4 10.5 1.2 0.5 -2.3 -1.1 -1.1 -0.7 Turkey 6.7 6.5 0.2 -0.1 0.4 -0.5 0.8 -0.3 Uganda 1.9 5.3 1.2 -0.4 0.0 0.4 0.0 0.1 United Arab Emirates 5.6 0.0 1.1 0.0 -3.4 -0.4 2.8 0.6 United States 3.3 6.0 0.5 -0.5 0.3 1.0 1.7 1.7 Uruguay 6.4 4.8 0.8 0.1 2.9 0.7 7.6 1.8 Venezuela 8.5 6.8 0.2 0.3 -2.3 -1.1 -0.8 -0.4 Zambia 6.0 5.3 2.3 -0.4 1.5 0.8 0.2 0.1 Zimbabwe 7.9 11.5 2.7 -0.5 3.5 1.4 2.1 0.8